9 citations · 10 across the 2 of their papers we have counts for
3 papers
cs.LG2020★ 1 cited
Interventional Domain Adaptation
Jun Wen, Changjian Shui, Kun Kuang +4
Domain adaptation (DA) aims to transfer discriminative features learned from source domain to target domain. Most of DA methods focus on enhancing feature transferability through d…
cs.LG2019★ 9 cited
Bayesian Uncertainty Matching for Unsupervised Domain Adaptation
Jun Wen, Nenggan Zheng, Junsong Yuan +2
Domain adaptation is an important technique to alleviate performance degradation caused by domain shift, e.g., when training and test data come from different domains. Most existin…
cs.LG2018
Exploiting Local Feature Patterns for Unsupervised Domain Adaptation
Jun Wen, Risheng Liu, Nenggan Zheng +3
Unsupervised domain adaptation methods aim to alleviate performance degradation caused by domain-shift by learning domain-invariant representations. Existing deep domain adaptation…